Accelerating MATLAB Performance: 1001 tips to speed up by Yair M. Altman

By Yair M. Altman

The MATLAB® programming setting is frequently perceived as a platform compatible for prototyping and modeling yet no longer for "serious" purposes. one of many major lawsuits is that MATLAB is too gradual.

Accelerating MATLAB Performance goals to right this notion through describing a number of how one can enormously increase MATLAB application pace. jam-packed with millions of important information, it leaves no stone unturned, discussing each point of MATLAB.

Ideal for newcomers and pros alike, the e-book describes MATLAB functionality in a scale and intensity by no means earlier than released. It takes a complete method of MATLAB functionality, illustrating quite a few how you can reach the specified speedup.

The publication covers MATLAB, CPU, and reminiscence profiling and discusses quite a few tradeoffs in functionality tuning. It describes the application in MATLAB of commonplace tuning recommendations utilized in the software program undefined, in addition to tools which are particular to MATLAB reminiscent of utilizing varied information forms or integrated functions. 

The ebook discusses MATLAB vectorization, parallelization (implicit and explicit), optimization, reminiscence administration, chunking, and caching. It explains MATLAB's reminiscence version and info the way it will be leveraged. It describes using GPU, MEX, FPGA, and other kinds of compiled code, in addition to recommendations for rushing up deployed functions. It info particular information for MATLAB GUI, images, and I/O. It additionally experiences a wide selection of utilities, libraries, and toolboxes which could aid to enhance performance.

Sufficient info is supplied to permit readers to right away follow the feedback to their very own MATLAB courses. wide references also are integrated to permit those that desire to extend the remedy of a selected subject to take action easily.

Supported via an energetic site and various code examples, the ebook may also help readers quickly reach major mark downs in improvement expenditures and software run occasions.

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Extra info for Accelerating MATLAB Performance: 1001 tips to speed up MATLAB programs

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2. 37 We can do this by inserting deliberate pause calls,† or by only displaying feedback once every few steps. 2 Placing the User in Control Enable the user to choose (possibly via some preference option, or maybe a GUI control) between Fast/Default/Comprehensive processing. This way, the user is in control of the performance, and can choose whether to sacriice accuracy for performance, or vice versa. This throttling control reduces user frustration and aligns expectations with the results. In fact, users will be much more likely to accept a slow-running computation if they are placed in charge and consciously choose the “Comprehensive” option.

3. 6. ‡ Computer scientist Ken Thompson’s famous quote: “When in doubt, use brute force”. 3 for one speciic utilization of this concept. 2. 3, a special case of this. Ken Thompson again: “One of my most productive days was throwing away 1000 lines of code”. * Instead of spending time optimizing the intermediate steps, spend the effort to avoid or merge them. • Bottom-up optimization — Many performance hotspots are caused by underlying factors that are not reported in the proiling result. For example, if the Proiler may report much time spent in some I/O function, we might be tempted to tune that function.

In other cases it was simply a relection of improved algorithmic understanding, since he too was learning new methods over the years. Finally, computers themselves have gotten vastly more capable: what was once a super-computer now sits on every desktop, and modern phones are smarter than the computers on the Apollo lunar modules. 4 What to Tune So we have decided that we need to improve our program’s performance. Good for us. But what exactly is it that we wish to improve? In other words, which “performance” exactly are we trying to tune?

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